1. Field of the Invention
The present invention generally relates to semantic objects. More particularly, the present invention relates to indexing, searching and retrieving of semantic objects.
2. Description of the Related Art
Exemplarily, the petroleum industry collects and archives many terabytes of data in the process of exploration for oil and gas resources. This data includes seismic surveys, formation micro imaging, core sample photography, well log data and the like. Search and retrieval of seismic data archives of this data present one of the most difficult challenges due to the requirements of domain specific knowledge and the large volume of data.
Land and sea based seismic surveys are commonly acquired during the process of oil and gas exploration. Most of the existing research in this domain has focused on enhancing features and visualization techniques for the seismic data that is generated from these surveys in order to assist geologists in tasks, such as constructing 3D reservoir models. Once a geologist hypothesizes a reservoir model, it can then be used to choose precise locations for drilling and extraction. However, the amount of seismic data is very large. Therefore, it is very difficult to search and to analyze the seismic data to identify seismic regions that have specific geological characteristics (such as sand channels, strong horizons, faults, etc) in an interactive application.
Indeed, the large amount of seismic data often involves mounting several tapes of tertiary storage to sequentially load the data into a visualization workstation. Once the data has been loaded, a geologist can view and browse the images created directly from the raw seismic data in a manner that is quite similar to the way one might view meteorological data. Using the visualization provided by these systems, a geologist might view successive slices of depth in the data. However, like a common weather map with values such as temperature, wind speed, and precipitation in each city, the seismic data is simply a set of values at each point in space. In both the domains of weather and petroleum geology, an interpreter (such as, for example, a meteorologist or geologist) interprets the data and creates “semantic objects.” In meteorology, examples of such semantic objects include “cold front,” “low pressure system” or “hurricane.” In petroleum geology, geologists are similarly interested in “horizons,” “faults,” “sand channels,” “reservoirs,” and the like.
In a visualization system, a user simply views representations of the raw data on a display, and may make annotations that are saved by the system so that they can be retrieved later.
Additionally, even with these systems that enable a petroleum geologist to visualize the raw geologic data, an enormous amount of data is presented and it can be very difficult for a petroleum geologist to identify features in the geology that is being visualized.
Further, the amount of data that is collected has also outpaced the ability for current systems and/or geologists to analyze and even for these systems to store the data.
While the petroleum industry has been exemplarily described above, other industries which analyze, collect and/or store large amounts of data have similar problems.